main.py

import dash
from dash import html
from dash import dcc
from dash.dependencies import Input, Output, State
import dash_bootstrap_components as dbc
import business_logic as bl
import layout_configs as lc
import support_functions as sf

#############################################################################
# Style modifications
#############################################################################
CONTENT_STYLE = {
    "margin-left": "2rem",
    "margin-right": "2rem",
}

TEXT_STYLE = {"textAlign": "center"}

DROPDOWN_STYLE = {"textAlign": "left"}

#############################################################################
# Content
#############################################################################
# Reference cards for bottom disclosures
# References relating to DEACOT report

deacot_reference_card = (
    dbc.Card(
        [
            dbc.CardBody(
                [
                    dbc.Button("?", id="deacot_card_open", color="dark"),
                    dbc.Modal(
                        [
                            dbc.ModalHeader("DEACOT Report References"),
                            dbc.ModalBody(
                                [
                                    html.P(
                                        "Speculators are traders with a commercial interest in the underlying commodity"
                                    ),
                                    html.P(
                                        "Funds are traders with no commercial interest in the underlying commodity"
                                    ),
                                    html.P(
                                        "Others / Non-Reporting are aggregated traders not required to individually register positions"
                                    ),
                                    html.P(
                                        "Dashed lines signify short position levels."
                                    ),
                                    html.P("Data retrieved from CFTC.gov:"),
                                    dbc.CardLink(
                                        "DEACOT Report",
                                        href="https://www.cftc.gov/files/dea/history/deacot2021.zip",
                                    ),
                                ]
                            ),
                            dbc.ModalFooter(
                                dbc.Button(
                                    "Close",
                                    id="deacot_card_close",
                                    className="ml-auto",
                                )
                            ),
                        ],
                        id="deacot_card_modal",
                    ),
                ]
            ),
        ],
        style={"width": "5rem"},
    ),
)


# References relating to Disaggregation report
da_reference_card = (
    dbc.Card(
        [
            dbc.CardBody(
                [
                    dbc.Button("?", id="da_reference_card_open", color="dark"),
                    dbc.Modal(
                        [
                            dbc.ModalHeader("Disaggregation Report References"),
                            dbc.ModalBody(
                                [
                                    html.P(
                                        "A “producer / merchant / processor / user” is an entity that predominantly engages in the production, processing, packing or handling of a physical commodity."
                                    ),
                                    html.P(
                                        "A “swap dealer” is an entity that deals primarily in swaps for a commodity. The swap dealer counterparties may be speculative traders, like hedge funds, or traditional commercial clients."
                                    ),
                                    html.P(
                                        "A “money manager” is a registered commodity trading advisor (CTA); a registered commodity pool operator (CPO); or an unregistered fund identified by CFTC."
                                    ),
                                    html.P(
                                        "Every other reportable trader that is not placed into one of the other three categories is placed into the “other reportables” category."
                                    ),
                                    html.P("Data retrieved from CFTC.gov:"),
                                    dbc.CardLink(
                                        "Disaggregation Report",
                                        href="https://www.cftc.gov/files/dea/history/fut_disagg_txt_2021.zip",
                                    ),
                                ]
                            ),
                            dbc.ModalFooter(
                                dbc.Button(
                                    "Close",
                                    id="da_reference_card_close",
                                    className="ml-auto",
                                )
                            ),
                        ],
                        id="da_reference_card_modal",
                    ),
                ]
            )
        ],
        style={"width": "5rem"},
    ),
)

# References relating to 3D surface for all
# Populates da_3d_legend_row - unused for now
da_reference_card_3d = (
    dbc.Card(
        [
            dbc.CardBody(
                [
                    dbc.Button("?", id="surface_card_open", color="dark"),
                    dbc.Modal(
                        [
                            dbc.ModalHeader("DA 3D Report Reference"),
                            dbc.ModalBody(
                                [
                                    html.P(
                                        [
                                            "Pr: Producer",
                                            html.Br(),
                                            "SD: Swap Dealer",
                                            html.Br(),
                                            "MM: Money Manager",
                                            html.Br(),
                                            "NR: Non-reporting",
                                            html.Br(),
                                            "Ot: Other",
                                        ]
                                    ),
                                    html.P(
                                        [
                                            "L: long positions / Demand",
                                            html.Br(),
                                            "S: short positions / Supply",
                                            html.Br(),
                                            "Net: long minus short",
                                        ]
                                    ),
                                ]
                            ),
                            dbc.ModalFooter(
                                dbc.Button(
                                    "Close",
                                    id="surface_card_close",
                                    className="ml-auto",
                                )
                            ),
                        ],
                        id="surface_card_modal",
                    ),
                ]
            )
        ],
        style={"width": "5rem"},
    ),
)


# Create drop-down selector
future_select = dbc.Row(
    [
        dbc.Col(
            [
                html.Div(
                    [
                        dcc.Dropdown(
                            id="future",
                            options=[{"label": i, "value": i} for i in bl.da_list],
                            value="SILVER - COMMODITY EXCHANGE INC.",
                        ),
                    ],
                    className="dash-bootstrap",
                ),
            ],
            md=6,
        )
    ]
)

# Info Bar
info_bar = html.Div(
    id="summary",
)

# Container for sentiment charts
sentiment_direction = dbc.Row(
    [
        dbc.Col(
            dcc.Graph(
                id="deacot_sent",
                style={"height": "70vh"},
                config=lc.tool_config,
            ),
            md=11,
        ),
        dbc.Col(
            html.Div(deacot_reference_card),
            md=1,
        ),
    ]
)

# This is a busy chart so give it its own row
DA_direction = dbc.Row(
    [
        dbc.Col(
            dcc.Graph(
                id="da_sent",
                style={"height": "70vh"},
                config=lc.tool_config,
            ),
            md=11,
        ),
        dbc.Col(
            html.Div(da_reference_card),
            md=1,
        ),
    ]
)

# Container for postion charts
da_postiions = dbc.Row(
    [
        dbc.Col(
            dcc.Graph(
                id="da_pos_all",
                style={"height": "70vh"},
                config=lc.tool_config,
            ),
            md=6,
        ),
        dbc.Col(
            dcc.Graph(
                id="da_pos_pct",
                style={"height": "70vh"},
                config=lc.tool_config,
            ),
            md=6,
        ),
    ]
)


# Container for 3d Net Postion Chart
da_3d_positions = dbc.Row(
    [
        dbc.Col(
            [
                dcc.Graph(
                    id="da_3d_net",
                    style={"height": "70vh"},
                    config=lc.tool_config,
                ),
                dcc.RangeSlider(
                    id="da_3d_net_range_slider",
                    min=bl.df_da["week_number"].min(),
                    max=bl.df_da["week_number"].max(),
                    value=[
                        bl.df_da["week_number"].min(),
                        bl.df_da["week_number"].max(),
                    ],
                    allowCross=False,
                ),
            ],
            md=6,
        ),
        # dbc.Col(
        #     html.Div(da_reference_card_3d),
        #     align="center",
        #     md=1,
        # ),
        dbc.Col(
            [
                dcc.Graph(
                    id="da_3d_all",
                    style={"height": "70vh"},
                    config=lc.tool_config,
                ),
                dcc.RangeSlider(
                    id="da_3d_all_range_slider",
                    min=bl.df_da["week_number"].min(),
                    max=bl.df_da["week_number"].max(),
                    value=[
                        bl.df_da["week_number"].min(),
                        bl.df_da["week_number"].max(),
                    ],
                    allowCross=False,
                ),
            ],
            md=6,
        ),
    ]
)

# Currently unused.  Can't quite get a formatting I like
# sticking a pin in it for now.
da_3d_legend_row = dbc.Row(
    [
        dbc.Col(
            md=5,
        ),
        dbc.Col(
            html.Div(da_reference_card_3d),
            align="center",
            md=2,
        ),
        dbc.Col(
            md=5,
        ),
    ]
)

# Container for relative change bar charts
da_diffs = dbc.Row(
    [
        dbc.Col(
            dcc.Graph(
                id="da_diff_all",
                style={"height": "75vh"},
                config=lc.tool_config,
            ),
            md=6,
        ),
        dbc.Col(
            dcc.Graph(
                id="da_diff_pct",
                style={"height": "75vh"},
                config=lc.tool_config,
            ),
            md=6,
        ),
    ]
)

# Container for the latest week position bar chart
da_pos_snap = dbc.Row(
    [
        dbc.Col(
            dcc.Graph(
                id="da_bar",
                style={"height": "75vh"},
                config=lc.tool_config,
            ),
            md=12,
        ),
    ]
)


# Container to put the reference row together
references = dbc.Row(
    [
        dbc.Col(
            html.Div(deacot_reference_card),
            md=6,
        ),
        dbc.Col(
            html.Div(da_reference_card),
            md=6,
        ),
    ]
)


####################################################
# Layout Creation Section
####################################################
main_page = html.Div(
    [
        html.Hr(),
        html.H5("Futures Market Comparison and Analysis", style=TEXT_STYLE),
        html.Hr(),
        future_select,
        html.Hr(),
        info_bar,
        html.Hr(),
        sentiment_direction,
        html.Hr(),
        DA_direction,
        html.Hr(),
        da_postiions,
        html.Hr(),
        da_3d_positions,
        html.Hr(),
        da_pos_snap,
        html.Hr(),
        da_diffs,
        html.Hr(),
    ],
    style=CONTENT_STYLE,
)

#############################################################################
# Application parameters
#############################################################################
app = dash.Dash(
    __name__,
    suppress_callback_exceptions=True,
    external_stylesheets=[dbc.themes.CYBORG],
)
app.config.suppress_callback_exceptions = True
app.title = "CFTC Data Analysis"
app.layout = html.Div(
    [dcc.Location(id="url", refresh=False), html.Div(id="page-content")]
)

# Multi-page selector callback - not really used, but left in for future use
@app.callback(Output("page-content", "children"), Input("url", "pathname"))
def display_page(pathname):
    # Left in because I'm not sure if this will be a muli-page app at some point

    # if pathname == "/market-sentiment":
    #     return volumes
    # else:
    return main_page


####################################################
#  Callbacks - Modals
####################################################
# Deacot Reference Card
@app.callback(
    Output("deacot_card_modal", "is_open"),
    [
        Input("deacot_card_open", "n_clicks"),
        Input("deacot_card_close", "n_clicks"),
    ],
    [State("deacot_card_modal", "is_open")],
)
def toggle_modal(n1, n2, is_open):
    if n1 or n2:
        return not is_open
    return is_open


# DA Reference card
@app.callback(
    Output("da_reference_card_modal", "is_open"),
    [
        Input("da_reference_card_open", "n_clicks"),
        Input("da_reference_card_close", "n_clicks"),
    ],
    [State("da_reference_card_modal", "is_open")],
)
def toggle_modal(n1, n2, is_open):
    if n1 or n2:
        return not is_open
    return is_open


# DA Reference card
@app.callback(
    Output("surface_card_modal", "is_open"),
    [
        Input("surface_card_open", "n_clicks"),
        Input("surface_card_close", "n_clicks"),
    ],
    [State("surface_card_modal", "is_open")],
)
def toggle_modal(n1, n2, is_open):
    if n1 or n2:
        return not is_open
    return is_open


####################################################
#  Callbacks - charts
####################################################

# Sentiment charts
@app.callback(
    dash.dependencies.Output("deacot_sent", "figure"),
    [dash.dependencies.Input("future", "value")],
)
def deacot_sentiment(future1):
    df1 = bl.df_deacot[bl.df_deacot["Exchange"] == future1]
    df1.set_index("Date", inplace=True)

    arr = df1["commodity"].unique()
    asset = arr[0]

    fig = sf.make_sentiment_chart(df1, asset)
    return fig


@app.callback(
    dash.dependencies.Output("da_sent", "figure"),
    [dash.dependencies.Input("future", "value")],
)
def all_positions_da(future1):
    df1 = bl.df_da[bl.df_da["Exchange"] == future1]
    df1.set_index("Date", inplace=True)

    arr = df1["commodity"].unique()
    asset = arr[0]

    fig = sf.make_chart_DA(df1, asset, "Contracts")
    return fig


# Positions Charts
@app.callback(
    dash.dependencies.Output("da_pos_all", "figure"),
    [dash.dependencies.Input("future", "value")],
)
def net_positions_actual_da(future1):
    df1 = bl.df_da[bl.df_da["Exchange"] == future1]
    df1.set_index("Date", inplace=True)

    arr = df1["commodity"].unique()
    asset = arr[0]

    fig = sf.make_net_DA_pos(df1, asset, "Contracts")
    return fig


@app.callback(
    dash.dependencies.Output("da_pos_pct", "figure"),
    [dash.dependencies.Input("future", "value")],
)
def net_positions_pct_da(future1):
    df1 = bl.df_da[bl.df_da["Exchange"] == future1]
    df1.set_index("Date", inplace=True)

    arr = df1["commodity"].unique()
    asset = arr[0]

    fig = sf.make_net_DA(df1, asset, "Contracts")
    return fig


# 3d postiion chart
@app.callback(
    dash.dependencies.Output("da_3d_net", "figure"),
    [
        dash.dependencies.Input("future", "value"),
        dash.dependencies.Input("da_3d_net_range_slider", "value"),
    ],
)
def da_3d_position_net(future1, week):
    # Rangeslider - set initial values if none are set
    if week is None:
        first_week = bl.df_da["week_number"].min()
        last_week = bl.df_da["week_number"].max()
    else:
        first_week = week[0]
        last_week = week[1]

    df1 = bl.df_da[bl.df_da["Exchange"] == future1]

    # Rangeslider - filter by the selected slide ends
    df1 = df1[(df1["week_number"] >= first_week) & (df1["week_number"] <= last_week)]
    df1.set_index("Date", inplace=True)

    arr = df1["commodity"].unique()
    asset = arr[0]

    fig = sf.da_3d_surface(df1, asset)
    return fig


# 3d postiion chart for all positions
@app.callback(
    dash.dependencies.Output("da_3d_all", "figure"),
    [
        dash.dependencies.Input("future", "value"),
        dash.dependencies.Input("da_3d_all_range_slider", "value"),
    ],
)
def da_3d_position_all(future1, week):
    # Rangeslider - set initial values if none are set
    if week is None:
        first_week = bl.df_da["week_number"].min()
        last_week = bl.df_da["week_number"].max()
    else:
        first_week = week[0]
        last_week = week[1]

    df1 = bl.df_da[bl.df_da["Exchange"] == future1]

    # Rangeslider - filter by the selected slide ends
    df1 = df1[(df1["week_number"] >= first_week) & (df1["week_number"] <= last_week)]
    df1.set_index("Date", inplace=True)

    arr = df1["commodity"].unique()
    asset = arr[0]

    fig = sf.da_3d_surface_all(df1, asset)
    return fig


# Week-over-week diffs in positions charts
@app.callback(
    dash.dependencies.Output("da_diff_all", "figure"),
    [dash.dependencies.Input("future", "value")],
)
def diff_position_actual_barchart_da(future1):
    df1 = bl.df_da[bl.df_da["Exchange"] == future1]
    df1.set_index("Date", inplace=True)

    arr = df1["commodity"].unique()
    asset = arr[0]
    df = df1.iloc[-2:]

    fig = sf.make_diff_barchart_DA_actual(df, asset, "Contracts")
    return fig


@app.callback(
    dash.dependencies.Output("da_diff_pct", "figure"),
    [dash.dependencies.Input("future", "value")],
)
def diff_position_pct_barchart_da(future1):
    df1 = bl.df_da[bl.df_da["Exchange"] == future1]
    df1.set_index("Date", inplace=True)

    arr = df1["commodity"].unique()
    asset = arr[0]
    df = df1.iloc[-2:]
    fig = sf.make_diff_barchart_DA(df, asset, "Contracts")
    return fig


# Total position breakdown chart
@app.callback(
    dash.dependencies.Output("da_bar", "figure"),
    [dash.dependencies.Input("future", "value")],
)
def total_position_barchart_da(future1):
    df1 = bl.df_da[bl.df_da["Exchange"] == future1]
    df1.set_index("Date", inplace=True)

    arr = df1["commodity"].unique()
    asset = arr[0]
    df = df1.iloc[-1:]

    fig = sf.make_barchart_DA(df, asset, "Contracts")
    return fig


###################################################
# Summary Block
###################################################
@app.callback(
    dash.dependencies.Output("summary", "children"),
    [dash.dependencies.Input("future", "value")],
)
def dashboard_summary_numbers(future1):
    # Grab some values from the most recent DA datafame
    df1 = bl.df_da[bl.df_da["Exchange"] == future1]
    df1.set_index("Date", inplace=True)

    # I only care about the most recent row so pull it
    #  It makes reference easier further down.
    df = df1.iloc[-1:]

    # Return the entire structured block
    return html.Div(
        dbc.Row(
            [
                dbc.Col(
                    dbc.Alert(
                        [
                            html.H6("Latest Date: "),
                            html.H6(df.index),
                        ],
                        color="light",
                    ),
                    md=2,
                ),
                dbc.Col(
                    dbc.Alert(
                        [
                            html.H6("Open Interest: "),
                            html.H6(df.Open_Interest),
                        ],
                        color="success",
                    ),
                    md=2,
                ),
                dbc.Col(
                    dbc.Alert(
                        [
                            html.H6("Total Reporting Long: "),
                            html.H6(df.total_report_long_all),
                        ],
                        color="primary",
                    ),
                    md=2,
                ),
                dbc.Col(
                    dbc.Alert(
                        [
                            html.H6("Total Reporting Short: "),
                            html.H6(df.total_report_short_all),
                        ],
                        color="warning",
                    ),
                    md=2,
                ),
                dbc.Col(
                    dbc.Alert(
                        [
                            html.H6("Total Non-Reporting Long: "),
                            html.H6(df.nonreport_long_all),
                        ],
                        color="primary",
                    ),
                    md=2,
                ),
                dbc.Col(
                    dbc.Alert(
                        [
                            html.H6("Total Non-Reporting Short: "),
                            html.H6(df.nonreport_short_all),
                        ],
                        color="warning",
                    ),
                    md=2,
                ),
            ]
        )
    )


###################################################
# Server Run
###################################################
if __name__ == "__main__":
    app.run_server(debug=True, host="0.0.0.0", port=8050, dev_tools_hot_reload=True)